Search NASA⌕ Search

SEARCH · Search NASA

Results for “Data Characterization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Methane on Mars: New Insights into the Sensitivity of CH4 with the NOMAD/ExoMars Spectrometer Through Its First In-Flight Calibration

The Nadir and Occultation for MArs Discovery instrument (NOMAD), onboard the ExoMars Trace Gas Orbiter (TGO) spacecraft was conceived to observe Mars in solar occultation, nadir, and limb geometries, and will be able to produce an outstanding amount of diverse data, mostly focused on properties of the atmosphere. The infrared channels of the instrument operate by combining an echelle grating spectrometer with an Acousto- Optical Tunable Filter (AOTF). Using in-flight data, we characterized the instrument performance and parameterized its calibration. In particular: an accurate frequency calibration was achieved, together with its variability due to thermal effects on the grating. The AOTF properties and transfer function were also quantified, and we developed and tested a realistic method to compute the spectral continuum transmitted through the coupled grating and AOTF system. The calibration results enabled unprecedented insights into the important problem of the sensitivity of NOMAD to methane abundances in the atmosphere. We also deeply characterized its performance under realistic conditions of varying aerosol abundances, diverse albedos and changing illumination conditions as foreseen over the nominal mission. The results show that, in low aerosol conditions, NOMAD single spectrum, 1σ sensitivity to CH4 is around 0.33 ppbv at 20 km of altitude when performing solar occultation's, and better than 1 ppbv below 30 km. In dusty conditions, we show that the sensitivity drops to 0 below 10 km. In Nadir geometry, results demonstrate that NOMAD will be able to produce seasonal maps of CH4 with a sensitivity around 5 ppbv over most of planet's surface with spatial integration over 5×5° bins. Results show also that such numbers can be improved by a factor of ~10 to ~30 by data binning. Overall, our results quantify NOMAD's capability to address the variable aspects of Martian climate.

Liuzzi, Giuliano↗
DOE OSTI2025

Multi-head physics-informed neural networks for learning functional priors and uncertainty quantification

In numerous applications, the integration of prior knowledge and historical information is essential, particularly for tasks requiring the solution of ordinary or partial differential equations (ODEs/PDEs) in data-sparse or noisy environments. For instance, achieving accurate solutions to time-dependent PDEs with limited initial condition measurements necessitates an effective strategy for embedding prior knowledge. Hard-parameter sharing architectures in neural networks (NNs) have demonstrated success in both traditional and scientific machine learning domains, facilitating the learning of informative representations. Here, in this study, we introduce a novel, yet efficient, method to enhance physics-informed neural networks (PINNs) by incorporating a multi-head structure that enables the learning of functional priors from both empirical data and governing physical laws. This prior information can then be used to address data sparsity and high-level noise in solving ODE/PDE problems with uncertainty quantification (UQ). The approach, termed Multi-Head PINN (MH-PINN), consists of a shared body NN and multiple head NNs, each corresponding to an individual PINN instance. Our framework for functional prior learning is carried out in two stages: (1) training the MH-PINNs to develop a shared body NN alongside multiple head NNs, and (2) employing these trained head NNs to estimate a prior distribution through a normalizing flow-based density estimator. The learned functional prior can then be applied as a regularization mechanism in deterministic contexts or as an informative prior within a Bayesian inference framework, aiding in the resolution of subsequent ODE/PDE tasks. We evaluate the efficacy of MH-PINNs across five benchmark problems, including a high-dimensional parametric PDE, all characterized by data sparsity or substantial noise levels. Our findings reveal that MH-PINNs deliver accurate solutions and robust UQ, demonstrating adaptability across a range of complex and challenging scenarios.

Bayesian inference↗
DOE OSTI2024

Providing Experimental Infrastructure for Accelerating Advanced Reactor Demonstrations through the National Reactor Innovation Center

A suite of experimental infrastructure projects has been developed by the National Reactor Innovation Center to accelerate advanced reactor demonstrations and facilitate their development, addressing crucial gaps in data, materials characterization, and modeling. First, the Molten Salt Thermophysical Examination Capability (MSTEC) provides a specialized platform for post-irradiation characterization of molten salt reactor fuel, coolant salts, and structural materials, essential for supporting the design and operation of advanced reactors and future commercial molten salt reactor development and licensing. The Virtual Test Bed (VTB) complements these efforts by leveraging advanced modeling and simulation tools to evaluate reactor performance and safety. Serving as a library of reference models, the VTB offers a database of multiphysics reactor models, facilitating rapid safety evaluations and includes continuous software quality assurance, crucial for accelerating deployment while maintaining reliability. Additionally, the Helium Component Test Facility (HeCTF) addresses the need for high-temperature helium-cooled reactor component testing. As the first-of-its-kind facility in the United States, HeCTF emulates high-temperature gas reactor conditions, reducing time and cost associated with component validation, thereby accelerating reactor development. Finally, In-cell Thermal Creep Frames provide a unique solution for obtaining thermal creep data from irradiated materials, critical for materials qualification and licensing. Developed by the National Reactor Innovation Center, these compact frames enable the examination of previously irradiated materials, overcoming traditional limitations and enhancing the understanding of mechanical properties crucial for reactor development. Collectively, these experimental infrastructure projects form a comprehensive framework aimed at expediting advanced reactor demonstrations, fostering innovation, and ensuring the viability of next-generation nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2004

"Smart" Magnetic Fluids Experiment Operated on the International Space Station

InSPACE is a microgravity fluid physics experiment that was operated on the International Space Station (ISS) in the Microgravity Science Glovebox from late March 2003 through early July 2003. (InSPACE is an acronym for Investigating the Structure of Paramagnetic Aggregates From Colloidal Emulsions.) The purpose of the experiment is to obtain fundamental data of the complex properties of an exciting class of smart materials termed magnetorheological (MR) fluids. MR fluids are suspensions, or colloids, comprised of small (micrometer-sized) superparamagnetic particles in a nonmagnetic medium. Colloids are suspensions of very small particles suspended in a liquid. (Examples of other colloids are blood, milk, and paint.) These controllable fluids can quickly transition into a nearly solid state when exposed to a magnetic field and return to their original liquid state when the magnetic field is removed. Controlling the strength of the magnetic field can control the relative stiffness of these fluids. MR fluids can be used to improve or develop new seat suspensions, robotics, clutches, airplane landing gear, and vibration damping systems. The principal investigator for InSPACE is Professor Alice P. Gast of the Massachusetts Institute of Technology (MIT). The InSPACE hardware was developed at the NASA Glenn Research Center. The InSPACE samples were delivered to the ISS in November 2002, on the Space Shuttle Endeavour, on Space Station Utilization Flight UF-2/STS113. Operations began on March 31, 2003, with the processing of three different particle size samples at multiple test parameters. This investigation focused on determining the structural organization of MR colloidal aggregates when exposed to a pulsing magnetic field. On Earth, the aggregates take the shape of footballs with spiky tips. This characteristic shape may be influenced by the pull of gravity, which causes most particles initially suspended in the fluid to sediment, (i.e., settle and collect at the bottom of the cell). In the absence of sedimentation effects on the ISS, the behavior and shape of these MR aggregate structures are dominated exclusively by magnetic and surface tension forces. The microscopic detail of these structures was imaged under two orthogonal camera views. The video was downlinked to the InSPACE team at Glenn's Telescience Support Center and to MIT and also recorded onboard the ISS on videotapes that will be brought back to the ground by the space shuttles. The study examined the effect on the structure formation by varying the magnetic field strength and pulse frequency, and particle size. Fundamental data that characterized the structure formation were obtained. InSPACE completed its last planned test run on July 2, 2003. Operations occurred on 21 days over approximately a 3-month period. Forty-one test points were completed during 26 test runs. During the initial testing, the procedures followed by the crew were modified to maximize the observation of some unexpected and interesting aggregate behavior. As a result Dr. Gast has reported on the formation of aggregate shapes that are more extended and diverse than those observed on the ground. Sheets of magnetic material folded over in a labyrinth pattern and large columnar aggregates with complex interfaces with the surrounding fluid are examples of the interesting structures that have been observed on the ISS. In light of these early findings, the understanding of the fundamental properties of MR fluids on the basis of ground-based observations may need to be reconsidered.The experiments on the ISS have provided a vast amount of video data for analysis. While this analysis is ongoing, plans are being made for additional experimental runs. For this purpose, additional hardware and cells containing samples of different magnetic particles and sizes are being fabricated for a future launch to the ISS. The InSPACE hardware will remain on orbit until this testing is completed.

Agui, Juan H.↗
DOE OSTI2024

Genomic and environmental controls on Castellaniella biogeography in an anthropogenically disturbed subsurface

Castellaniella species have been isolated from a variety of mixed-waste environments including the nitrate and multiple metal-contaminated subsurface at the Oak Ridge Reservation (ORR). Previous studies examining microbial community composition and nitrate removal at ORR during biostimulation efforts reported increased abundances of members of the Castellaniella genus concurrent with increased denitrification rates. Thus, we asked how genomic and abiotic factors control the Castellaniella biogeography at the site to understand how these factors may influence nitrate transformation in an anthropogenically impacted setting. We report the isolation and characterization of several Castellaniella strains from the ORR subsurface. Five of these isolates match at 100% identity (at the 16S rRNA gene V4 region) to two Castellaniella amplicon sequence variants (ASVs), ASV1 and ASV2, that have persisted in the ORR subsurface for at least 2 decades. However, ASV2 has consistently higher relative abundance in samples taken from the site and was also the dominant blooming denitrifier population during a prior biostimulation effort. We found that the ASV2 representative strain has greater resistance to mixed metal stress than the ASV1 representative strains. We attribute this resistance, in part, to the large number of unique heavy metal resistance genes identified on a genomic island in the ASV2 representative genome. Additionally, we suggest that the relatively lower fitness of ASV1 may be connected to the loss of the nitrous oxide reductase (nos) operon (and associated nitrous oxide reductase activity) due to the insertion at this genomic locus of a mobile genetic element carrying copper resistance genes. This study demonstrates the value of integrating genomic, environmental, and phenotypic data to characterize the biogeography of key microorganisms in contaminated sites.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2016

Frequency-Range Distribution of Boulders Around Cone Crater: Relevance to Landing Site Hazard Avoidance

Boulders represent a landing hazard that must be addressed in the planning of future landings on the Moon. A boulder under a landing leg can contribute to deck tilt and boulders can damage spacecraft during landing. Using orbital data to characterize boulder populations at locations where landers have safely touched down (Apollo, Luna, Surveyor, and Chang'e-3 sites) is important for determining landing hazard criteria for future missions. Additionally, assessing the distribution of boulders can address broader science issues, e.g., how far craters distribute boulders and how this distribution varies as a function of crater size and age. The availability of new Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images [1] enables the use of boulder size- and range frequency distributions for a variety of purposes [2-6]. Boulders degrade over time and primarily occur around young or fresh craters that are large enough to excavate bedrock. Here we use NAC images to analyze boulder distributions around Cone crater (340 m diameter) at the Apollo 14 site. Cone crater (CC) was selected because it is the largest crater where astronaut surface photography is available for a radial traverse to the rim. Cone crater is young (approximately 29 Ma [7]) relative to the time required to break down boulders [3,8], giving us a data point for boulder range-frequency distributions (BRFDs) as a function of crater age.

Clegg-Watkins, R. N.↗
NASA NTRSDate not supplied

Characterization of OCO-2 and ACOS-GOSAT biases and errors for flux estimates

We characterize the magnitude of seasonally and spatially varying biases in the National Aeronautics and Space Administration (NASA) Orbiting Carbon Observatory-2 (OCO-2) Version 8 (v8) and the Atmospheric CO2 Observations from Space (ACOS) Greenhouse Gas Observing SATellite (GOSAT) version 7.3 (v7.3) satellite CO2 retrievals by comparisons to measurements collected by the Total Carbon Column Observing Network (TCCON), Atmospheric Tomography (ATom) experiment, and National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL) and U. S. Department of Energy (DOE) aircraft, and surface stations. Although the ACOS-GOSAT estimates of the column averaged carbon dioxide (CO2) dry air mole fraction (XCO2) have larger random errors than the OCO-2 XCO2 estimates, and the space-based estimates over land have larger random errors than those over ocean, the systematic errors are similar across both satellites and surface types, 0.6 ± 0.1 ppm. We find similar estimates of systematic error whether dynamic versus geometric coincidences or ESRL/DOE aircraft versus TCCON are used for validation (over land), once validation and co-location errors are accounted for. We also find that areas with sparse throughput of good quality data (due to quality flags and preprocessor selection) over land have ~double the error of regions of high-throughput of good quality data. We characterize both raw and bias-corrected results, finding that bias correction improves systematic errors by a factor of 2 for land observations and improves errors by ~0.2 ppm for ocean. We validate the lowermost tropospheric (LMT) product for OCO-2 and ACOS-GOSAT by comparison to aircraft and surface sites, finding systematic errors of ~1.1 ppm, while having 2-3 times the variability of XCO2. We characterize the time and distance scales of correlations for OCO-2 XCO2 errors, and find error correlations on scales of 0.3 degrees, 5-10 degrees, and 60 days. We find comparable scale lengths for the bias correction term. Assimilation of the OCO-2 bias correction term is used to estimate flux errors resulting from OCO-2 seasonal biases, finding annual flux errors on the order of 0.3 and 0.4 PgC/yr for Transcom-3 ocean and land regions, respectively.

Susan S Kulawik↗
DOE OSTI2022

Characterization of modeling and experimental data inconsistencies from burst testing for high-burnup commercial fuel rod applications

Fuel fragmentation, relocation, and dispersal are some of the largest issues remaining in the nuclear industry before rod-average burnup can be increased beyond 62 GWd/tU. The issue is primarily related to the potential for fuel to be dispersed into the reactor primary system, which may increase public risk. One way to prevent dispersal is to avoid cladding burst. The objective of this work is to support the high burnup safety case by evaluating cladding burst under high-burnup, full-length fuel rods and to identify uncertainties that could improve model predictions. The results of this analysis will evaluate realistic, prototypic loss-of-coolant accident (LOCA) conditions; support future cladding burst test designs; and inform the development of mechanistic material models. Realistic high-burnup operating conditions were implemented in the BISON fuel performance code to simulate steady-state and LOCA transient fuel rod evolution to the point at which cladding burst occurred. Parametric studies are performed to assess code response to changes in rod internal pressures and heating rates. Results were compared with simulated LOCA experiments to identify inconsistencies between commercial fuel rod analysis and experimental validation. The representative full-length fuel rod LOCA simulation results did not agree with cladding burst tests. Cladding burst tests indicated burst occurring well below (100–150 °C) those calculated in the full-length fuel rod LOCA analysis. Further investigation indicated that the cladding burst tests do not appear to be representative for full-length fuel rods. The inconsistency investigated in this work showed that the differences between the BISON simulation and the experiment's cladding burst conditions arise from an incomplete characterization of the cladding surface temperature, detailed rodlet characterization, lack of cladding strain measurements, and uncertainty in the cladding creep and failure models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

High Performance Data Analytics on a Commodity Private Cloud

Sandia is researching novel methods of analysis for large datasets. The term “Big Data” has been used frequently in recent years to describe a discipline of computer science that attempts to distil an increasing quantity of data into a result or meaningful subset that can be easily visualized and acted upon by human consumers. These data are frequently characterized by one or more of the following: high volume, velocity, variety, and veracity. Sandia scientists and researchers are no strangers to large datasets, which often typify the result of high-performance computing workloads. The challenge for Sandia data scientists, however, comes at the arrival of exascale computing, which has become mandated by executive order for national computing centers. Because of power and networking limitations, exascale computing precludes the movement of datasets at exascale from data production to data analysis. Such analysis must be done in-situ, to mitigate the time and power costs of network transport. Currently, many of Sandia’s data analytics environments exist as independent entities, often specialized for individual use cases, interconnected to other data analytics, high-performance computing, and storage systems. Sandia is procuring, installing, and researching future platforms for such data analytics. A memory footprint of 256 GB per node, fourteen data rate (FDR) InfiniBand networking, PCIe connected non-volatile memory (NVMe) data storage, and an object data store will characterize the coming institutional data analytics platforms. The combined systems will contain 300 compute nodes. A cloud-inspired software stack resulting from collaboration between the Sandia centers will allow the systems to support a flexible mix of user and system-facing workloads and use cases including code development and testing in R and Python, Apache Hadoop and Spark, distributed in-memory databases, graph analytics, emulytics, system log and predictive analytics, and data visualization for institutional and mission customers. These systems will arrive at the end of FY 2015 and production is planned by the spring of FY 2016.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2000

BOREAS RSS-19 1994 Seasonal Understory Reflectance Data

The BOREAS RSS-19 team collected airborne remotely sensed images and ground reflectance data for characterizing the radiometric properties of the boreal forest landscape. One objective of BOREAS is to further the understanding of the spectral bidirectional reflectance of typical boreal ecosystem stands in the visible/near-infrared regime. An essential input for any canopy BRDF model is an accurate estimate of the average understory reflectance, both for sunlit and shaded conditions. These variables can be expected to vary seasonally because of species-dependent differences in the phenological cycle of foliar display. In response to these requirements, the average understory reflectance for the flux tower sites of both the NSA (Thompson, Manitoba) and the SSA (Candle Lake, Saskatchewan) was observed throughout the year during five field campaigns. This was done by measuring the nadir reflectance (400 to 850 nm) of sunlit and shaded understory (vegetation and snow cover) along a surveyed LAI transect line (Chen, RSS-07) at each site near solar noon and documenting an average site reflectance. Comparisons between sites reveal differences in the green and infrared regions of the spectra, because of the differing species in the understory for each site. Temporal (seasonal) variation for each site was also observed (06-Feb-1994 to 16-Sep-1994), indicating the changing flora mixtures and changing spectral signatures as the understory matures during the growing season. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Miller, John R.↗
NASA NTRS2006

Assessment of Postflight Locomotor Performance Utilizing a Test of Functional Mobility: Strategic and Adaptive Responses

Space flight induces adaptive modification in sensorimotor function, allowing crewmembers to operate in the unique microgravity environment. This adaptive state, however, is inappropriate for a terrestrial environment. During a re-adaptation period upon their return to Earth, crewmembers experience alterations in sensorimotor function, causing various disturbances in perception, spatial orientation, posture, gait, and eye-head coordination. Following long duration space flight, sensorimotor dysfunction would prevent or extend the time required to make an emergency egress from the vehicle; compromising crew safety and mission objectives. We are investigating two types of motor learning that may interact with each other and influence a crewmember's ability to re-adapt to Earth's gravity environment. In strategic learning, crewmembers make rapid modifications in their motor control strategy emphasizing error reduction. This type of learning may be critical during the first minutes and hours after landing. In adaptive learning, long-term plastic transformations occur, involving morphological changes and synaptic modification. In recent literature these two behavioral components have been associated with separate brain structures that control the execution of motor strategies: the strategic component was linked to the posterior parietal cortex and the adaptive component was linked to the cerebellum (Pisella, et al. 2004). The goal of this paper was to demonstrate the relative contributions of the strategic and adaptive components to the re-adaptation process in locomotor control after long duration space flight missions on the International Space Station (ISS). The Functional Mobility Test (FMT) was developed to assess crewmember s ability to ambulate postflight from an operational and functional perspective. Sixteen crewmembers were tested preflight (3 sessions) and postflight (days 1, 2, 4, 7, 25) following a long duration space flight (approx 6 months) on the ISS. We have further analyzed the FMT data to characterize strategic and adaptive components during the postflight readaptation period. Crewmembers walked at a preferred pace through an obstacle course set up on a base of 10 cm thick medium density foam (Sunmate Foam, Dynamic Systems, Inc., Leicester, NC). The 6.0m X 4.0m course consisted of several pylons made of foam; a Styrofoam barrier 46.0cm high that crewmembers stepped over; and a portal constructed of two Styrofoam blocks, each 31cm high, with a horizontal bar covered by foam and suspended from the ceiling which was adjusted to the height of the crewmember s shoulder. The portal required crewmembers to bend at the waist and step over a barrier simultaneously. All obstacles were lightweight, soft and easily knocked over. Crewmembers were instructed to walk through the course as quickly and as safely as possible without touching any of the objects on the course. This task was performed three times in the clockwise direction and three times in the counterclockwise direction that was randomly chosen. The dependent measures for each trial were: time to complete the course (seconds) and the number of obstacles touched or knocked down. For each crewmember, the time to complete each FMT trial from postflight days 1, 2, 4, 7 and 25 were further analyzed. A single logarithmic curve using a least squares calculation was fit through these data to produce a single comprehensive curve (macro). This macro curve composed of data spanning 25 days, illustrates the re-adaptive learning function over the longer time scale term. Additionally, logarithmic curves were fit to the 6 data trials within each individual post flight test day to produce 5 separate daily curves. These micro curves, produced from data obtained over the course of minutes, illustrates the strategic learning function exhibited over a relative shorter time scale. The macro curve for all subjects exhibited adaptive motor learning patterns over the 25 day period. Howev, 9/16 crewmembers exhibited significant strategic motor learning patterns in their micro curves, as defined by m > 1 in the equation of the line y=m*LN(x) +b. These data indicate that postflight recovery in locomotor function involves both strategic and adaptive mechanisms. Future countermeasures will be designed to enhance both recovery processes.

Warren, L. E.↗
NASA NTRS1992

SSME improved characterization using highly instrumented engine test data

This paper discusses the analysis of Space Shuttle Main Engine (SSME) 3001 test data and its applications to steady-state models. Engine 3001 is a highly instrumented Phase II (current configuration) SSME that was tested at the Technology Test Bed facility located at Marshall Space Flight Center. A test series covering a carefully selected range of operating conditions was performed during 1991. An analysis of pressure, temperature and flowrate data was performed to evaluate the ability of steady-state models to accurately characterize the internal system of an SSME. Much of the special instrumentation was used to acquire data never before measured at the engine level prior to Engine 3001 testing. The analysis revealed that modifications are needed to improve model calculations of internal Hydrogen and Oxygen flows. Modifying steady-state models to more accurately simulate the internal flow system of an SSME should improve both engine performance evaluations and prediction capabilities.

Piekarski, Brian↗
DOE OSTI2016

Correlations between jets and charged particles in PbPb and pp collisions at $ \sqrt{s_{\mathrm{NN}}}=2.76 $ TeV

The quark-gluon plasma is studied via medium-induced changes to correlations between jets and charged particles in PbPb collisions compared to pp reference data. This analysis uses data sets from PbPb and pp collisions with integrated luminosities of 166 μb –1 and 5.3 pb –1 , respectively, collected at $\sqrt{s_{\mathrm{NN}}}=2.76$ TeV. The angular distributions of charged particles are studied as a function of relative pseudorapidity (Δη) and relative azimuthal angle (ΔΦ) with respect to reconstructed jet directions. Charged particles are correlated with all jets with transverse momentum ($p_{\mathrm{T}}$) above 120 GeV, and with the leading and subleading jets (the highest and second-highest in $p_{\mathrm{T}}$, respectively) in a selection of back-to-back dijet events. Modifications in PbPb data relative to pp reference data are characterized as a function of PbPb collision centrality and charged particle $p_{\mathrm{T}}$. A centrality-dependent excess of low-$p_{\mathrm{T}}$ particles is present for all jets studied, and is most pronounced in the most central events. This excess of low-$p_{\mathrm{T}}$ particles follows a Gaussian-like distribution around the jet axis, and extends to large relative angles of Δη ≈ 1 and ΔΦ ≈ 1.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

NRAP-open-IAM: A flexible open-source integrated-assessment-model for geologic carbon storage risk assessment and management

Large-scale implementation of geologic carbon storage (GCS) to help reduce atmospheric greenhouse gas emissions requires stakeholder confidence that injected CO2 will remain contained and that potential subsurface environmental risks are acceptably small and manageable. The U.S. Department of Energy’s National Risk Assessment Partnership (NRAP) has developed an open-source integrated assessment model (NRAP-Open-IAM) to help address questions about a potential GCS site’s ability to effectively contain injected CO 2 and protect groundwater and other overlying environmentally sensitive receptors. NRAP-Open-IAM allows a user to: (1) incorporate relevant site geologic and injection scenario data; (2) characterize important site features and events;(3) couple fast prediction models of various system components of the engineered geologic system; and (4) execute stochastic, dynamic simulation of whole GCS system performance, leakage risk assessment, and uncertainty quantification. NRAP-Open-IAM is available on GitLab (https://gitlab.com/NRAP/OpenIAM), and is accompanied by multiple application examples and detailed user and developer guides.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Surrogate models for development of unconventional shale reservoirs by an integrated numerical approach of hydraulic fracturing, flow and geomechanics, and machine learning

We develop well-completion surrogate models by taking an integrated workflow of hydraulic fracturing, flow, geomechanics, and machine learning simulation. There are three steps in the proposed workflow. First, history-matching processes are conducted with the field data including pumping and production data for characterization. Second, full-physics simulation is performed with various parameters of the field development (e.g., cluster spacing, clusters per stage, pumping rates and times, amount of proppant, and well spacing) to generate multiple simulation results by changing the parameters of the completion design with well-known hydraulic fracturing, reservoir, geomechanics simulators to calculate fracture geometry, reservoir depressurization, induced stress changes. The workflow is demonstrated over a field in the Southern Midland Basin. Here, we take two completion scenarios: a single well case followed by a multi-well case. Finally, a Long Short-Term Memory (LSTM) machine learning algorithm is employed to create surrogate models that can replicate the full-physics simulation results. Furthermore, results show that the trained models applied in the single well and multi-well cases for a particular geological system can provide good accuracy close to those provided by full-physics simulations. Specifically, the site-specific surrogate models can predict fracture parameters (length, height, and surface area) and cumulative production accurately with computational efficiency, suggesting our proposed workflow can be used as a pragmatic tool for expediting the well completion optimization process.

Geomechanics↗
DOE OSTI2021

Practice Consolidation Among U.S. Radiation Oncologists Over Time

Health care practices across the United States have been consolidating in response to various market forces. The degree of practice consolidation varies widely across specialties but has not been well studied within radiation oncology. This study used Medicare data to characterize the extent of practice consolidation among radiation oncologists and to investigate associated market factors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

A Phage Foundry Framework to Systematically Develop Viral Countermeasures to Combat Antibiotic-Resistant Bacterial Pathogens

At its current rate, the rise of antimicrobial-resistant (AMR) infections is predicted to paralyze our industries and healthcare facilities while becoming the leading global cause of loss of human life. With limited new antibiotics on the horizon, we need to invest in alternative solutions. Bacteriophages (phages)–viruses targeting bacteria–offer a powerful alternative approach to tackle bacterial infections. Despite recent advances in using phages to treat recalcitrant AMR infections, the field lacks systematic development of phage therapies scalable to different applications. We propose a Phage Foundry framework to establish metrics for phage characterization and to fill the knowledge and technological gaps in phage therapeutics. Coordinated investment in AMR surveillance, sampling, characterization, and data sharing procedures will enable rational exploitation of phages for treatments. A fully realized Phage Foundry will enhance the sharing of knowledge, technology, and viral reagents in an equitable manner and will accelerate the biobased economy.

59 BASIC BIOLOGICAL SCIENCES↗